{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 数据探索"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "数据集共9个字段:  \n",
    "pregnants：怀孕次数  \n",
    "Plasma_glucose_concentration：口服葡萄糖耐量试验中2小时后的血浆葡萄糖浓度  \n",
    "blood_pressure：舒张压，单位:mm Hg  \n",
    "Triceps_skin_fold_thickness：三头肌皮褶厚度，单位：mm  \n",
    "serum_insulin：餐后血清胰岛素，单位:mm  \n",
    "BMI：体重指数（体重（公斤）/ 身高（米）^2）  \n",
    "Diabetes_pedigree_function：糖尿病家系作用  \n",
    "Age：年龄  \n",
    "Target：标签， 0表示不发病，1表示发病  \n",
    "  \n",
    "离散型特征：pregnants/Age  \n",
    "表示方法：sns.countplot(),df.valuecount()  \n",
    "  \n",
    "连续型特征：  Plasma_glucose_concentration/blood_pressure/Triceps_skin_fold_thickness/serum_insulin/BMI/Diabetes_pedigree_function  \n",
    "表示方法：sns.displot(),DataFrame.hist(),sns.boxplot(),sns.violinplot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>pregnants</th>\n",
       "      <th>Plasma_glucose_concentration</th>\n",
       "      <th>blood_pressure</th>\n",
       "      <th>Triceps_skin_fold_thickness</th>\n",
       "      <th>serum_insulin</th>\n",
       "      <th>BMI</th>\n",
       "      <th>Diabetes_pedigree_function</th>\n",
       "      <th>Age</th>\n",
       "      <th>Target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>6</td>\n",
       "      <td>148</td>\n",
       "      <td>72</td>\n",
       "      <td>35</td>\n",
       "      <td>0</td>\n",
       "      <td>33.6</td>\n",
       "      <td>0.627</td>\n",
       "      <td>50</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>85</td>\n",
       "      <td>66</td>\n",
       "      <td>29</td>\n",
       "      <td>0</td>\n",
       "      <td>26.6</td>\n",
       "      <td>0.351</td>\n",
       "      <td>31</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8</td>\n",
       "      <td>183</td>\n",
       "      <td>64</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>23.3</td>\n",
       "      <td>0.672</td>\n",
       "      <td>32</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>89</td>\n",
       "      <td>66</td>\n",
       "      <td>23</td>\n",
       "      <td>94</td>\n",
       "      <td>28.1</td>\n",
       "      <td>0.167</td>\n",
       "      <td>21</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>137</td>\n",
       "      <td>40</td>\n",
       "      <td>35</td>\n",
       "      <td>168</td>\n",
       "      <td>43.1</td>\n",
       "      <td>2.288</td>\n",
       "      <td>33</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   pregnants  Plasma_glucose_concentration  blood_pressure  \\\n",
       "0          6                           148              72   \n",
       "1          1                            85              66   \n",
       "2          8                           183              64   \n",
       "3          1                            89              66   \n",
       "4          0                           137              40   \n",
       "\n",
       "   Triceps_skin_fold_thickness  serum_insulin   BMI  \\\n",
       "0                           35              0  33.6   \n",
       "1                           29              0  26.6   \n",
       "2                            0              0  23.3   \n",
       "3                           23             94  28.1   \n",
       "4                           35            168  43.1   \n",
       "\n",
       "   Diabetes_pedigree_function  Age  Target  \n",
       "0                       0.627   50       1  \n",
       "1                       0.351   31       0  \n",
       "2                       0.672   32       1  \n",
       "3                       0.167   21       0  \n",
       "4                       2.288   33       1  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train=pd.read_csv('pima-indians-diabetes.csv')      #读入csv文件\n",
    "train.head()      "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 768 entries, 0 to 767\n",
      "Data columns (total 9 columns):\n",
      "pregnants                       768 non-null int64\n",
      "Plasma_glucose_concentration    768 non-null int64\n",
      "blood_pressure                  768 non-null int64\n",
      "Triceps_skin_fold_thickness     768 non-null int64\n",
      "serum_insulin                   768 non-null int64\n",
      "BMI                             768 non-null float64\n",
      "Diabetes_pedigree_function      768 non-null float64\n",
      "Age                             768 non-null int64\n",
      "Target                          768 non-null int64\n",
      "dtypes: float64(2), int64(7)\n",
      "memory usage: 54.1 KB\n"
     ]
    }
   ],
   "source": [
    "train.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>pregnants</th>\n",
       "      <th>Plasma_glucose_concentration</th>\n",
       "      <th>blood_pressure</th>\n",
       "      <th>Triceps_skin_fold_thickness</th>\n",
       "      <th>serum_insulin</th>\n",
       "      <th>BMI</th>\n",
       "      <th>Diabetes_pedigree_function</th>\n",
       "      <th>Age</th>\n",
       "      <th>Target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>3.845052</td>\n",
       "      <td>120.894531</td>\n",
       "      <td>69.105469</td>\n",
       "      <td>20.536458</td>\n",
       "      <td>79.799479</td>\n",
       "      <td>31.992578</td>\n",
       "      <td>0.471876</td>\n",
       "      <td>33.240885</td>\n",
       "      <td>0.348958</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>3.369578</td>\n",
       "      <td>31.972618</td>\n",
       "      <td>19.355807</td>\n",
       "      <td>15.952218</td>\n",
       "      <td>115.244002</td>\n",
       "      <td>7.884160</td>\n",
       "      <td>0.331329</td>\n",
       "      <td>11.760232</td>\n",
       "      <td>0.476951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.078000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>99.000000</td>\n",
       "      <td>62.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>27.300000</td>\n",
       "      <td>0.243750</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>117.000000</td>\n",
       "      <td>72.000000</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>30.500000</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>0.372500</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>6.000000</td>\n",
       "      <td>140.250000</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>127.250000</td>\n",
       "      <td>36.600000</td>\n",
       "      <td>0.626250</td>\n",
       "      <td>41.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>17.000000</td>\n",
       "      <td>199.000000</td>\n",
       "      <td>122.000000</td>\n",
       "      <td>99.000000</td>\n",
       "      <td>846.000000</td>\n",
       "      <td>67.100000</td>\n",
       "      <td>2.420000</td>\n",
       "      <td>81.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        pregnants  Plasma_glucose_concentration  blood_pressure  \\\n",
       "count  768.000000                    768.000000      768.000000   \n",
       "mean     3.845052                    120.894531       69.105469   \n",
       "std      3.369578                     31.972618       19.355807   \n",
       "min      0.000000                      0.000000        0.000000   \n",
       "25%      1.000000                     99.000000       62.000000   \n",
       "50%      3.000000                    117.000000       72.000000   \n",
       "75%      6.000000                    140.250000       80.000000   \n",
       "max     17.000000                    199.000000      122.000000   \n",
       "\n",
       "       Triceps_skin_fold_thickness  serum_insulin         BMI  \\\n",
       "count                   768.000000     768.000000  768.000000   \n",
       "mean                     20.536458      79.799479   31.992578   \n",
       "std                      15.952218     115.244002    7.884160   \n",
       "min                       0.000000       0.000000    0.000000   \n",
       "25%                       0.000000       0.000000   27.300000   \n",
       "50%                      23.000000      30.500000   32.000000   \n",
       "75%                      32.000000     127.250000   36.600000   \n",
       "max                      99.000000     846.000000   67.100000   \n",
       "\n",
       "       Diabetes_pedigree_function         Age      Target  \n",
       "count                  768.000000  768.000000  768.000000  \n",
       "mean                     0.471876   33.240885    0.348958  \n",
       "std                      0.331329   11.760232    0.476951  \n",
       "min                      0.078000   21.000000    0.000000  \n",
       "25%                      0.243750   24.000000    0.000000  \n",
       "50%                      0.372500   29.000000    0.000000  \n",
       "75%                      0.626250   41.000000    1.000000  \n",
       "max                      2.420000   81.000000    1.000000  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从结果中我们可以看到很多列的最小值为0。而在一些特定列代表的变量中，0值并没有意义，这就表名该值无效或为缺失值。\n",
    "\n",
    "具体来说，下列变量的最小值为0时数据无意义：\n",
    "1、血浆葡萄糖浓度\n",
    "2、舒张压\n",
    "3、肱三头肌皮褶厚度\n",
    "4、餐后血清胰岛素\n",
    "5、体重指数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Plasma_glucose_concentration      5\n",
      "blood_pressure                   35\n",
      "Triceps_skin_fold_thickness     227\n",
      "serum_insulin                   374\n",
      "BMI                              11\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "NaN_col_names = ['Plasma_glucose_concentration','blood_pressure','Triceps_skin_fold_thickness','serum_insulin','BMI']\n",
    "print((train[NaN_col_names] == 0).sum())    #输出特征缺失数据量"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3.4缺失值较多，1.2.5的缺失值较少  \n",
    "根据缺失值数量选择不同的填充策略"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 查看特征分布"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0,0.5,'number of occurance')"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x207a6ec3160>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# label\n",
    "sns.countplot(train['Target'])\n",
    "plt.xlabel('Daibetes')\n",
    "plt.ylabel('number of occurance')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0,0.5,'number of occurance')"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x207aa6663c8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# pregnants\n",
    "sns.countplot(train['pregnants'])\n",
    "plt.xlabel('number of pregnants')\n",
    "plt.ylabel('number of occurance')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x207aa6c3908>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x207aa530f98>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#怀孕次数与目标之间的关系\n",
    "sns.countplot(x=\"pregnants\", hue=\"Target\",data=train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "怀孕次数越多，患病几率越高"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0,0.5,'Number of occurrences')"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x207aaa50048>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plasma_glucose_concentration\n",
    "fig = plt.figure()\n",
    "sns.distplot(train.Plasma_glucose_concentration, kde = False)\n",
    "plt.xlabel('Plasma_glucose_concentration')\n",
    "plt.ylabel('Number of occurrences')    #需要进行缺失值处理"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x207aaa430f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.violinplot(x='Target', y='Plasma_glucose_concentration', data=train, hue=\"Target\")   #对通过x分类后的y分别画一个琴形图\n",
    "plt.xlabel('Diabetes', fontsize=12)\n",
    "plt.ylabel('Plasma_glucose_concentration', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0,0.5,'Target')"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x207aab35780>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#blood_pressure\n",
    "fig=plt.figure()\n",
    "sns.distplot(train['blood_pressure'],kde=True)\n",
    "plt.xlabel('blood_pressure',fontsize=12)\n",
    "plt.ylabel('Target',fontsize=12)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x207aaaffb70>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(x='Target',y='blood_pressure',data=train,hue='Target')\n",
    "plt.xlabel('Diabetes', fontsize=12)\n",
    "plt.ylabel('blood_pressure', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "不满足条件的数据量较多"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0,0.5,'Target')"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x207aacb53c8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Triceps_skin_fold_thickness\n",
    "fig=plt.figure()\n",
    "sns.distplot(train['Triceps_skin_fold_thickness'],kde=True)\n",
    "plt.xlabel('Triceps_skin_fold_thickness',fontsize=12)\n",
    "plt.ylabel('Target',fontsize=12)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x207aab85390>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x207aac8a4e0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "TriDF = train.groupby(['Triceps_skin_fold_thickness', 'Target'])['Triceps_skin_fold_thickness'].count().unstack('Target').fillna(0)\n",
    "TriDF[[0,1]].plot(kind='bar', stacked=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "患病人数大多分布在中部"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0,0.5,'Target')"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x207aae84588>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#serum_insulin\n",
    "fig=plt.figure()\n",
    "sns.distplot(train['serum_insulin'],kde=True)\n",
    "plt.xlabel('serum_insulin',fontsize=12)\n",
    "plt.ylabel('Target',fontsize=12)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x207ab2440b8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#BMI                             \n",
    "fig=plt.figure()\n",
    "sns.distplot(train['BMI'],kde=True)\n",
    "plt.xlabel('BMI')\n",
    "plt.ylabel('number of occurance')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x207ab82a240>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(x='Target',y='BMI',data=train,hue='Target')\n",
    "plt.xlabel('Diabetes', fontsize=12)\n",
    "plt.ylabel('BMI', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x207aca82fd0>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x207aca27128>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "BMIDF = train.groupby(['BMI', 'Target'])['BMI'].count().unstack('Target').fillna(0)\n",
    "BMIDF[[0,1]].plot(kind='bar', stacked=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "BMI越高，患病几率越大"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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kIyYFM/uR9/iZqQsnPfWGBzje1j3lfRSGevvKOew63s72w60JjUNEktdoJYXVZlYDfNTMSs2sLHaZqgDTwbGWbpyDeVPcR2Goa1fMISczxAN1w8/tLCIyWlL4HpGB784g0gQ1dqkLPrT0Ud/cCZDwkkJxXhZXnz2bX245orGQRGRYIyYF59w3nXNLiYx1tNA5tyBmWTiFMaa8I83dwNT3Zh7Oe9fMp607rApnERmWnyapHzezFWZ2i7csn4rA0slgb+bZCWx9NGjdgjKqy/L5yfP1iQ5FRJKQnwHxPg38GKjylh+b2aeCDiydHG7upKooh5zMjESHQihkvHfNPJ7Z28j+kx2JDkdEkkymj33+EljnnOsAMLN/BJ4Bbg8ysFR238bXV+RuOtBETmboDa8nynvWzOfffr+bu57ax1euW5bocEQkifjpp2BAbK1kv/ea+NTc2UdJfvLMYDpzRi5/ds48Hnj+ECfb1TldRF7jJyncDWw0sy+b2ZeBZ4lMuiM+DDhHc1cfJfnJNbDsX128kN7+Ae5+al+iQxGRJOKnovlfgBuBU0ATcKNz7htBB5Yu2nvC9A+4pCopACysLOSqZbO495kDtHX3JTocEUkSvoa5cM5t9pqo/ptz7gU/7zGzu8yswcy2j7DdzOybZrbHzLaa2arxBJ4qmjsjX7ileclVUgC4+eJFtHWH+XGS1HWISOL5qWieqB8SmcLz3hG2XwUs8ZZ1wHe9x7TS3NkLkLCSwliV20uqCvnuE69y/bnzk640IyJTL7AB8ZxzTxK55TSS64B7XcSzQImZzQ4qnkQZLCkkW53CoKvOnk1bdx/f+N3uRIciIklg1KRgZhlm9ruAzj0XOBTzvN57bbg4bjKzOjOrO3HiREDhBKO5q5fcrBC5WYnvozCcWTNyef/aan707AH2NLQlOhwRSbBRbx855/rNrNPMip1z8Z7gd7hmrcOO6eycuwO4A2DNmjUpNe5zc2cfpUl+W6amvIDMkPGJH2/mhvMXvGH7B9ZVJyAqEUkEP3UK3cA2M/stEO0C65z79CTPXQ/Mj3k+DzgyyWMmnUgfheS8dTSoMCeTy8+oYsP2Y7xY38yKeSWJDklEEsRPUvi1t8TbQ8AtZvafRCqYW5xzaTdKW1NnL7UVBYkOY0zrF1Ww7XALD205woLyAmYkYWspEQnemEnBOXePmeUB1c65V/we2MzuBy4BKsysHvgSkOUd83vABuBqYA/QSaQvRFrp6u2nJzxAaZKXFAAyQsZ7Vs/n9sd38+AL9XxkfS1m6rguMt2MmRTM7O3A14BsYIGZrQS+4py7drT3OefeP8Z2B3xyHLGmnOauxDZHHa+KohzeetYs/nvrUTbuO8V5C8sTHZKITDE/TVK/DKwFmgGcc1uAN9ZGyhtEm6Om0K2Y8xaWc/rMIn699SgHGzWKqsh04ycphIdpeZRSLYAS5bWOa6mTFEJmvHfNfIrzs/jxcwdp1RAYItOKn6Sw3cw+AGSY2RIzux14OuC40kJzZx+ZIaMwJ8iO4/GXl53Bn6+robuvn/s2HtTUnSLTiJ+k8CngLKAHuB9oBW4NMqh00dTZS0l+dkpW2M4qzuU9q+dz6FQnt9z3AuH+gUSHJCJTwM8oqZ3Oub8DLgcudc79nXOuO/jQUl9TZ19KtDwaybK5xbx9xRx+t/M4f/+L7UTaBohIOvPT+uhc4C6gyHveAnzUObcp4NhSXlNnL3NLihMdxqSct7CcmvJ8bn9sD5VFOfz1W05PdEgiEiA/N7vvBD7hnPsjgJldSGTineVBBpbqesL9dPb2p3RJYdBtV5zGibaeaGL48PraRIckIgHxkxTaBhMCgHPuT2amkdPGEG2OWpAafRRGY2b8n3cs42R7L196aAflBTlcszztBrQVEUapUzCzVd7EN8+Z2b+b2SVmdrGZfQd4YsoiTFFNXnPUZB8Mz6/MjBDf+sA5rK4u5bMPbOGZVxsTHZKIBGC0iuave8tK4DQiw1R8GVgKrA88shTXNDjjWhrcPhqUm5XBDz6yhpryfG66t46XjrQmOiQRibMRbx855y6dykDSTXNHb0r2URhLSX4293x0Le/67tPccPdz/Pzj5zO/LD/RYYlInPhpfVQCfBiojd0/DkNnp7VU7qMwljkledzz0bW8+7tP85G7nuNnHz+f32w/Nub7NC+DSPLz03ltA5GEsA3YFLPIKFK9j8JYTptZxJ03nMvh5i5u/OHz9IbVuU0kHfi5t5HrnLst8EjSTDr0URjLubVl3P7+c7j5PzbR3z/A+9dWp2XJSGQ68VNS+JGZfczMZptZ2eASeGQpLJ36KIzlLWfN4vNXncH2I608uftkosMRkUnykxR6gX8GnuG1W0d1QQaV6tKpj4IfH3vTQs6eW8yjO46x+7i6sIikMj9J4TZgsXOu1jm3wFsWBh1YKku3PgpjMTPetWoeM2fk8kDdIQ23LZLC/NQp7CAyXab4lG59FO7beHDMfbIzQ1y/dj7ffnwPD27WdJ4iqcpPUugHtpjZ40SGzwbUJHU06dpHYSxVRblctWw2D714hGf3nWK9pvMUSTl+vrV+4S3iUzr3URjLugVlvHyslYe3HWVxZSGVRTmJDklExmHMpOCcu2cqAkkn6d5HYTSD9Qv/+rtd/GLLYf7ywgXTMjmKpKoxK5rNbJ+Z7R26TEVwqaqps3faVDIPpyg3iyvPms2+kx28cLA50eGIyDj4uX20JmY9F3gPoH4KI2jt7ov0UZgmzVFHsqa2lM0Hm9iw/SinzyqiYJrVr4ikKj/TcTbGLIedc98ALpuC2FLSwcZIQ63yaZ4UQma845y5dPf188iOscdFEpHk4GdAvFUxT0NESg5FgUWU4g4MJoXC6Z0UAGbNyOX8RRU8teck6xepJZJIKvBTpv96zHoY2A+8N5Bo0sD+xg4AyqZ5SWHQJadXsulAE7/ZfkzzO4ukAD+tjzSvwjgcaOygKCeTnMyMRIeSFPKzM7nsjCp+ve0of9h1gotPq0x0SCIyCj+3j3KAd/HG+RS+ElxYqWt/YydlunX0OusWlvHM3ka++uudXLi4goyQmqiKJCs/Yx/9EriOyK2jjphFhnGgsYPyAnXYipUZCvHWs2bxyvE2flp3KNHhiMgo/NQpzHPOXRl4JGmgq7ef4609nD23JNGhJJ1lc2awuqaUr/92F29fMUdNVEWSlJ+SwtNmdnbgkaSBg6fU8mgkZsbfXbOUE2093PGk+j6KJCs/SeFCYJOZvWJmW81sm5ltDTqwVDTY8mi691EYyarqUq5ZPps7ntzLsZbuRIcjIsPwkxSuApYAbwHeDrzNe5QhDkSTguoURvL5K8+gf8Dx9UdfSXQoIjIMPz2aDwy3TEVwqWZ/Yyel+VnkZas56kjml+XzkfNr+NnmenYcaUl0OCIyhJ+Sgvh0oLGD6vKCRIeR9G65dAnFeVl8dcNOnHOJDkdEYigpxNH+k53UlucnOoykV5yfxWcuX8JTexp5/JWGRIcjIjGUFOKkJ9zP0ZYualRS8OWD62pYUFHAVze8TLh/INHhiIgn0KRgZld6rZb2mNnnh9l+g5mdMLMt3vKXQcYTpPqmLgYcKin4lJ0Z4vNXncGehnbuf14d2kSSRWBJwcwygG8Tab10JvB+MztzmF0fcM6t9JYfBBVP0AZbHqmk4N9bzpzJ2gVlfOO3u2jt7kt0OCJCsCWFtcAe59xe51wv8J9EhstIS682RJLCggolBb/MjL+/ZimNHb185/FXEx2OiBBsUpgLxN4XqPdeG+pdXqe4n5nZ/ADjCdTuhjYqCrM1ZPY4LZ9XwjvPmctdT+3jkNcjXEQSJ8gBaIYbCnNo+8NfAfc753rM7GbgHoaZ1c3MbgJuAqiuro53nHGx63g7S6o099Bo7tt4cNjXT5tZxK+3HeUv7nmeR269CDONoiqSKEGWFOqB2F/+84AjsTt4U3z2eE+/D6we7kDOuTucc2ucc2sqK5NvPH7nHHsa2jltZmGiQ0lJxXlZXLF0JruOt/OrrUcTHY7ItBZkUngeWGJmC8wsG7geeCh2BzObHfP0WmBngPEE5khLN+09YRbPVElhotYvKmduSR5f+dUOWjpV6SySKIElBedcGLgFeITIl/1PnHM7zOwrZnatt9unzWyHmb0IfBq4Iah4grT7eBsAp1WppDBRITPeec5cmjr7+Idfv5TocESmrUAHtXfObQA2DHntizHrfwv8bZAxTIXdx9uByL1xmbg5JXl8/OJFfOvxPbx5aRVXLps99ptEJK7UozkOdh1vo6Iwh1K1PJq0z7x5CcvnFfP5B7dxvFXDa4tMNU1/FQe7VMkcNz+tq+fyM2byrcd388EfbOSG82sJxbRG+sC65Gx9JpIuVFKYJOcce463sUT1CXFTWZTD1WfPZk9DuwbME5liSgqTdKSlm47efpaoPiGu1taWcc78Eh7b2cAuryJfRIKnpDBJg19YqmSOLzPjupVzmTkjlweeP8Spjt5EhyQyLSgpTFK0OarqFOIuOzPEB9dV43Dc+8x+unr7Ex2SSNpTUpik3cfbqSzKoSRfLY+CUF6YwwfX1XCyvYf7nz9In+ZeEAmUksIkvXysTaWEgC2qLOSd58xlT0M7X/zlDk3hKRIgJYVJ6O7r5+VjrSyfV5LoUNLe6poyLj6tkvufO8j3/7g30eGIpC31U5iEl4620tfvWDlfSWEqXHHmTApzMvm/D79MdVkBVy6bleiQRNKOSgqTsOVgM4CSwhQJmfH1965gxbwSbn3gBV442JTokETSjkoKk7DlUDOzi3OZOSM30aFMGw9uPsxVy2ZxoLGDD/5gIzdftIiKopzX7aNezyITp5LCJLxY38wK1SdMuaLcLG68YAEAdz+9jzbN7ywSN0oKE3Sqo5cDjZ2srFZSSISKwhw+sr6W9p4w9zyzn54+9WEQiQclhQl6sT5Sn6CSQuLML8vn/WurOdbSzX3PHaR/QE1VRSZLSWGCthxsxgzOnlec6FCmtTNmzeAdK+eyu6GdBzfXqw+DyCQpKUzQi/XNnFZVRGGO6uoTbU1tGZcvreKFQ808+tLxRIcjktKUFCbAOceLh5pZMV+lhGRx2elVnFtbxh92neDeZ/YnOhyRlKWfuROw72QHTZ19rJxfmuhQxGNmXLtiDu3dfXzpoR2U5Gdz7Yo5iQ5LJOWopDABT+46AcD5i8oTHInEyggZ7zu3mnNry/jsA1v41YtHEh2SSMpRUpiAx145wcKKAmorChIdigyRnRni7hvOZXV1Kbc+sIWHlBhExkVJYZw6e8M8u7eRS06vSnQoMoKCnEzuvvFcVteU8un7X+Df//CqWiWJ+KSkME7PvNpIb3iAy85QUkhmBTmZ3PvRtbxt+Wz+78Mv84X/2ka3OriJjEkVzeP02MsN5GdncO4CVTInu9ysDL55/TnUlOfz7cdfpW5/E197zwpWaABDkRGppDAOzjmeeOUEFyyuICczI9HhiA+hkPE/3noGd994Lm3dYd75naf4u//axsHGzkSHJpKUlBTGYXdDO4ebu3TrKAVdenoVj3z2Ij6wrpqf1tVzydce569+VMdP6w7R0Nad6PBEkoZuH43D73c2AHDJ6ZUJjkQmojgvi//zjrP51GVLuOtP+/j55sM8siPSA7qqKIcFFQXMK82noiibysIcdh1vpzAnk8LcTApzMsnPziBkFj2ehuiWdKSk4NPAgOMndYc4p7qE2cV5iQ5HJmHmjFz+9uqlfO7KM3jpaCtP7TnJnoZ29p7s4JlXT3KyvZfe/oE3vC8rw5g5I5c5xXnUVuTz5qVVVGkuDUkzSgo+/XHPSfad7OAb71uZ6FAkTkIhY9ncYpbNff1wJc45WrvC3P30Ptp7wrR3h2nvCdPU0cvRlm62Hm7muf2n+EldPUtnz+Cas2dx9dmzWVhZmKArEYkfJQWf7n16PxWF2Vx1tuYFTnb3bTwYl+NUFeVSVfTG1wec42hLN682tLPzaCtfe3QXX3t0F7Nm5LJsbjHL5xVTURiZDU63mCTVKCn4cLCxk8deaeCWSxer1ZEQMmNuSR5zS/K46LRKWrr62H64hW2HW/jdzuP8budx5hTncva8Et60pIL5ZfmJDlnENyUFH/6AZA03AAAOS0lEQVRj4wFCZvrVJ8MqzsvigsUVXLC4gpauPrYdbmFbfTOP7DjGIzuOsWJ+CVcsreKS06s4c/YMQiEb+6AiCaKkMIaGtm7uf+4gbz1rpiqYZUzFeVlcuLiCCxdX0NTRS0aGsWHb0egtporCHC46rYKLT6vk/EUVVBblJDpkkddRUhjDl365g57wALddcXqiQ5EUU1qQzQfWVXPzxYs42d7Dk7tO8MQrJ3js5QYe3HwYgCVVhZQXZrOwopAFFQUUDDNpk0qoMpWUFEbx661HeXj7MT535RksrlLLEpm4isIc/mzVPP5s1Tz6BxzbD7fwzN5Gnnk1sjy79xQAs2bksrCygEWVhdSWF5CXrTosmVpKCiM42d7DF3+5nbPnFvOxNy1IdDiSokZrCTUjN4u3njWLNy+dSX1TJ3tPdrD3RDvP7TvF0682YsDc0jyOtnRx0WmVrJxfQlaGBiGQYCkpDONwcxcfunMj7T1h/undy8nUf0QJUEbIqCkvoKa8gEtPryLcP8DBpk72nuhgT0M73358D7c/toeinEzOX1zORadVctGSykBaNY3VnFe3stJfoEnBzK4E/g3IAH7gnPt/Q7bnAPcCq4FG4H3Ouf1BxjSWV461ccPdz9HeE+bej65l6ewZiQxHpqHMjBALKwpZWFHIm5fO5Jrls3l6z0me3H2CJ3edjA7NUV2Wz6rqEs6pLuW0mUUsriqkojAbM3+tm/r6B2jvDtPWHaa1u4/2njA7j7ZiRDr2ZYSMDDMyM4z87MhQH5L+LKjJR8wsA9gFXAHUA88D73fOvRSzzyeA5c65m83seuCdzrn3jXbcNWvWuLq6urjHe7i5i9t/v5ufbqqnrCCbe25cy5lzJpYQ4tV5SmQo5xwn2nvYfbydfSc7OHSqk7aecHR7blaIyqIcygpyyM0MkZ0ZItzv6Ozrp7u3n66+fjp7+2nv6aO7741DeYwlNytEeUEOFYXZVBblUFGYQ2VRzuvWBx8LsjN8J6hEGRhw/OjZA4T7HX0DA5HH/gHCA46w93jB4nL6ByAvK4O87BB5WZnkZWdQkJ1BUW4WuVmhpL9OADPb5JxbM9Z+Qab+tcAe59xeL6D/BK4DXorZ5zrgy976z4BvmZm5AKfJ6g0P0Nrdx7GWbg6e6uSlI638cc9JttU3kxkK8aHzavjEpYuoKtKYNpJ8zMzraZ3LBYsrIkNydIdpaO2moa2Hlq7IL/6OnjAtnY7wwAAZISM7I8TCygLviy2TIm+Qv9cesyjKzeSpPScB6B9wkcW5SFLpDdPe00+Hd+z2njA7jrTS1h15Ptx/2CyvhJGTGSIvK4PcrAxyskLkZmWwqrqUotxMZuRlUZSTSXZmiMyQkZUZIisUIhSCcH8k/t5w5DH2C7unr59n956KfpGHo1/kr325hwcGKCvIpic8QHffAD3hfnr6BugJv7Y+3BhXQ935p32jbs8wozg/ixm5r/0dZww+5kUei3Jf2z4jL2a795hMt6iDTApzgUMxz+uBdSPt45wLm1kLUA6cjHcwD287yq0PbKEn/Pp/BBkhY+X8Em65bAnXnzufOSXqiyCpw8wozsuiOC+LJTOHGZMjhp/6gAMTmGdiwLloomjvDtMWM15UZ28/3X39dIf7ae8Jc7I98vyFg0309cfnt9/gLa7MkJGZ4SWXjBCZGUZJPhTmZFJeEElIOZmRpJSTGSInM/L48tHWyPsyjKxQyDuW9+i9ZgZ9XlLqDQ/Q1+8ll75+usMDzCvNi96Ga+sOs/dkO61dYdq6++joHXvGv+zMEBkWuWUXssj3UkbIMIvcwnM4Bhx8ZH0Nt1y2JC5/t5EEmRSGK08N/VfgZx/M7CbgJu9pu5m9MsnYXmcv8CDw1/7fUkEAiSsJ6LpSy7iu64MBBhJn+rxGUAd8auJvr/GzU5BJoR6YH/N8HnBkhH3qzSwTKAZODT2Qc+4O4I6A4hw3M6vzc28u1ei6UouuK7WkynUFeSPreWCJmS0ws2zgeuChIfs8BHzEW3838FiQ9QkiIjK6wEoKXh3BLcAjRJqk3uWc22FmXwHqnHMPAXcCPzKzPURKCNcHFY+IiIwt0IbHzrkNwIYhr30xZr0beE+QMQQkaW5lxZmuK7XoulJLSlxXYP0UREQk9SRP41gREUk4JYVRmNmVZvaKme0xs88Psz3HzB7wtm80s9qpj3J8fFzTDWZ2wsy2eMtfJiLO8TKzu8yswcy2j7DdzOyb3nVvNbNVUx3jRPi4rkvMrCXm8/ricPslEzObb2aPm9lOM9thZp8ZZp+U+7x8Xlfyf17OOS3DLEQqx18FFgLZwIvAmUP2+QTwPW/9euCBRMcdh2u6AfhWomOdwLVdBKwCto+w/WrgYSJ9Y84DNiY65jhd1yXAfyc6znFe02xglbdeRGQ4nKH/DlPu8/J5XUn/eamkMLLoMB3OuV5gcJiOWNcB93jrPwMut+QeBMXPNaUk59yTDNPHJcZ1wL0u4lmgxMxmT010E+fjulKOc+6oc26zt94G7CQyukGslPu8fF5X0lNSGNlww3QM/YBfN0wHMDhMR7Lyc00A7/KK7D8zs/nDbE9Ffq89Fa03sxfN7GEzOyvRwYyHd8v1HGDjkE0p/XmNcl2Q5J+XksLI4jZMRxLxE++vgFrn3HLgd7xWEkp1qfZZ+bUZqHHOrQBuB36R4Hh8M7NC4OfArc651qGbh3lLSnxeY1xX0n9eSgojG88wHYw2TEcSGfOanHONzrke7+n3icx1kQ78fJ4pxznX6pxr99Y3AFlmVpHgsMZkZllEvjh/7Jx7cJhdUvLzGuu6UuHzUlIYWToO0zHmNQ25b3stkfui6eAh4MNeq5bzgBbn3NFEBzVZZjZrsB7LzNYS+T/dmNioRufFeyew0zn3LyPslnKfl5/rSoXPS1MpjcCl4TAdPq/p02Z2LRAmck03JCzgcTCz+4m07Kgws3rgS0AWgHPue0R61l8N7AE6gRsTE+n4+LiudwMfN7Mw0AVcn+Q/TAAuAD4EbDOzLd5rXwCqIaU/Lz/XlfSfl3o0i4hIlG4fiYhIlJKCiIhEKSmIiEiUkoKIiEQpKYiISJSSgoiIRCkpyISZWb83/O8ObyyX28ws5G1bY2bfHOP9N5jZt8Z5zi9MJuZ4M7MnzGyNt77BzEoSFMf93nhVn43jMS8xs/Njnt9sZh+O1/ElOanzmkxGl3NuJYCZVQH3ERnq40vOuTqgLoBzfgH4agDHnTTn3NXj2d/MMr2BFCfFzGYB5zvnaiZ7rCEuAdqBpyHa+UrSnEoKEhfOuQbgJuAWb2iCS8zsvyHSnd/MnjazF7zH02PeOt/MfmORiX++NPiimf25mT3nlUT+3cwyzOz/AXneaz8eZb8MM/uhmW03s22j/Xr2ful/w4truzf0AGZWYJEJbp734r7Oez3PzP7T+1X+AJAXc6z9g+PYmNn/MrOXzey33q/4v4k531fN7A/AZ8ys0sx+7p3neTO7YLTzj+BRoMr7G7xpSOmlwsz2e+s3mNmD3t97t5n9U0zsV5rZZq/E93uLjPJ5M/DZmON+OeY6VprZs97f4b/MrDTm+v7R+0x2mdmbRolbklGiJ3TQkroL0D7Ma03ATGImEwFmAJne+puBn3vrNwBHiQw3ngdsB9YAS4mM1prl7fcd4MNDzznSfkQG8fttzH4lo1zDE8D3vfWL8CazIVIa+fPB9xOZMKUAuI3I8CAAy4kMB7LGe74fqPCuYYt3TUXAbuBvYs73nZjz3wdc6K1XExk3Z8Tzj3ANtcRMwuOdYzCmCmB/zN97L5HSXC5wgMigc5VEhqle4O1X5j1+eTDuoc+BrcDF3vpXgG/EnPvr3vrVwO8S/e9Uy/gW3T6SeBtuyONi4B4zW0Jk+OOsmG2/dc41ApjZg8CFRL5oVwPPW2TssDygYZjjXj7Cfr8CFprZ7cCvifySHs39EJnQxsxmePUCbwGuHfxlTORLtJpI4vimt/9WM9s6zPEuBH7pnOvyrutXQ7Y/ELP+ZuBMe21uphlmVjTK+Sc7QOHvnXMtXlwvATVAKfCkc26fd12jjvRrZsVEEu0fvJfuAX4as8vg6KCbiCQsSSFKChI3ZrYQ6Cfyxbw0ZtM/AI87597p3ZZ4Imbb0MG3HJHEco9z7m/HOuVI+5nZCuCtwCeB9wIfHeU4I8XwLufcK0OOO9z+w8U1mo6Y9RCwfjCBxJxn2PP7FOa1W8O5Q7b1xKz3E/kOMOI7V8HgOQaPLylEdQoSF2ZWCXyPyPzOQ79gioHD3voNQ7ZdYWZlZpYHvAN4Cvg98G6v8hpv+2Alap9FxqxnpP28+/oh59zPgf9FZI7j0bzPe/+FRIZobiEykuynvC9nzOwcb98ngQ96ry0jcgtpqD8BbzezXItMuHLNKOd+FLhl8ImZrfRWRzq/H/t5bR6Md/vY/xngYjNb4J2rzHu9jcjtr9fx/j5NMfUFHwL+MHQ/SU3K4jIZeRYZIjiLyK/THwHDjSP/T0RuH90GPDZk25+89y0G7nORVkuY2d8Dj1qkiWsfkV/8B4A7gK1mttk598ER9usC7vZeAxirxNFkZk8TqfsYLFH8A/AN71xG5Iv2bcB3vWNvJVJv8NzQgznnnjezh4AXvZjriEzVOpxPA9/2jpdJJOncPMr5/fga8BMz+xBv/Hu/gXPuhJndBDzo/c0agCuI3Ib7mVfJ/akhb/sI8D0zyydST5EKQ1uLDxo6W6Y1M3uCSOVpXJvPmlmhc67d+9J8ErjJeZO6iyQzlRREgnGHmZ1J5J7+PUoIkipUUpBpwcy+TWRmrFj/5py7OxHxTISZvRX4xyEv73POvTMR8Uh6UlIQEZEotT4SEZEoJQUREYlSUhARkSglBRERiVJSEBGRqP8PyOAUiO69ndkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x207ac9645f8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Diabetes_pedigree_function\n",
    "fig=plt.figure()\n",
    "sns.distplot(train['Diabetes_pedigree_function'],kde=True)\n",
    "plt.xlabel('Diabetes_pedigree_function')\n",
    "plt.ylabel('number of occurance')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x207ac9c3390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(x='Target',y='Diabetes_pedigree_function',data=train,hue='Target')\n",
    "plt.xlabel('Diabetes', fontsize=12)\n",
    "plt.ylabel('Diabetes_pedigree_function', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x207acb54cf8>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x207acb17978>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "DiaDF = train.groupby(['Diabetes_pedigree_function', 'Target'])['Diabetes_pedigree_function'].count().unstack('Target').fillna(0)\n",
    "DiaDF[[0,1]].plot(kind='bar', stacked=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "22    72\n",
       "21    63\n",
       "25    48\n",
       "24    46\n",
       "23    38\n",
       "28    35\n",
       "26    33\n",
       "27    32\n",
       "29    29\n",
       "31    24\n",
       "41    22\n",
       "30    21\n",
       "37    19\n",
       "42    18\n",
       "33    17\n",
       "32    16\n",
       "36    16\n",
       "38    16\n",
       "45    15\n",
       "34    14\n",
       "40    13\n",
       "43    13\n",
       "46    13\n",
       "39    12\n",
       "35    10\n",
       "50     8\n",
       "44     8\n",
       "51     8\n",
       "52     8\n",
       "58     7\n",
       "47     6\n",
       "54     6\n",
       "57     5\n",
       "60     5\n",
       "48     5\n",
       "49     5\n",
       "53     5\n",
       "55     4\n",
       "62     4\n",
       "63     4\n",
       "66     4\n",
       "56     3\n",
       "59     3\n",
       "65     3\n",
       "67     3\n",
       "61     2\n",
       "69     2\n",
       "72     1\n",
       "64     1\n",
       "68     1\n",
       "70     1\n",
       "81     1\n",
       "Name: Age, dtype: int64"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Age  \n",
    "train['Age'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0,0.5,'frequency')"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x207ad0a8ba8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.distplot(train.Age, kde = False)\n",
    "plt.xlabel('Age')\n",
    "plt.ylabel('frequency')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x207ad1bef28>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x207ad29cf28>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "DF = train.groupby(['Age', 'Target'])['Age'].count().unstack('Target').fillna(0)\n",
    "DF[[0,1]].plot(kind='bar', stacked=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x207af290d68>"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x207af2d4d68>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data_corr = train.corr().abs()\n",
    "\n",
    "plt.subplots(figsize=(13, 9))\n",
    "sns.heatmap(data_corr,annot=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "数据之间的相关性较弱，年龄和血浆葡萄糖浓度"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
